Ciencia, tecnología e innovación

3D Printing Sensors on Human Skin. A one-of-a-kind 3D printer built at the University of Minnesota can print touch sensors directly on a model hand.

(Image courtesy of Shuang-Zhuang Guo/Michael McAlpine/University of Minnesota.) Engineering researchers at the University of Minnesota have developed a revolutionary process for 3D printing stretchable electronic sensory devices that could give robots the ability to feel their environment. The discovery is also a major step forward in printing electronics on real human skin. The research will be published in Advanced Materials and is currently online. "This stretchable electronic fabric we developed has many practical uses," said Michael McAlpine, a University of Minnesota mechanical engineering associate professor and lead researcher on the study.

The wrong neural path? How our understanding of the brain could be wrong. Understanding the human brain is arguably the greatest challenge of modern science.

The leading approach for most of the past 200 years has been to link its functions to different brain regions or even individual neurons (brain cells). But recent research increasingly suggests that we may be taking completely the wrong path if we are to ever understand the human mind. The idea that the brain is made up of numerous regions that perform specific tasks is known as “modularity”. And, at first glance, it has been successful. For example, it can provide an explanation for how we recognise faces by activating a chain of specific brain regions in the occipital and temporal lobes.

The difference between the two seems to be, more than anything else, a matter of priorities and emphasis. Mnuchin takes a narrow approach. He thinks that the problem of particular technologies called “artificial intelligence taking over American jobs” lies “far in the future.” And he seems to question the high stock-market valuations for “unicorns” – companies valued at or above $1 billion that have no record of producing revenues that would justify their supposed worth and no clear plan to do so. Summers takes a broader view. I think that Summers is right about the optics of Mnuchin’s statements. On the other hand, I sympathize with Mnuchin’s effort to warn non-experts against routinely investing in castles in the sky.
Deep Learning in 7 lines of code – Chatbot’s Life. The essence of machine learning is recognizing patterns within data.

This boils down to 3 things: data, software and math. What can be done in seven lines of code you ask? A lot. The way to reduce a deep learning problem to a few lines of code is to use layers of abstraction, otherwise known as ‘frameworks’. Today we’ll use tensorflow and tflearn. Abstraction is an essential property of software: the app you are using to view this piece is an abstraction layer above some operating system that knows how to read files, display images, etc. and this is an abstraction above lower level functions. Software frameworks are abstraction layers. Our reduction is achieved by using tflearn, a layer above tensorflow, a layer above a Python. Let’s start at the beginning. El mito del desempleo tecnológico Por Pablo Maas. Kevin Kelly and Steven Johnson on Where Ideas Come From. Say the word “inventor” and most people think of a solitary genius toiling in a basement.

But two ambitious new books on the history of innovation—by Steven Johnson and Kevin Kelly, both longtime wired contributors—argue that great discoveries typically spring not from individual minds but from the hive mind. In Where Good Ideas Come From: The Natural History of Innovation, Johnson draws on seven centuries of scientific and technological progress, from Gutenberg to GPS, to show what sorts of environments nurture ingenuity. He finds that great creative milieus, whether MIT or Los Alamos, New York City or the World Wide Web, are like coral reefs—teeming, diverse colonies of creators who interact with and influence one another.

Seven centuries are an eyeblink in the scope of Kelly’s book, What Technology Wants, which looks back over some 50,000 years of history and peers nearly that far into the future. Kevin Kelly: Our books are another case in point. Johnson: Exactly. Kelly: Right.
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